Senior Manager, Perception Data

Posted Yesterday
Be an Early Applicant
Foster City, CA, USA
Hybrid
339K-375K Annually
Senior level
Artificial Intelligence • Machine Learning • Robotics • Software • Transportation • Design • Manufacturing
Zoox is an autonomous mobility company that’s created a purpose-built robotaxi to give the world a better way to ride.
The Role
Leads Zoox’s perception data organization and data flywheel, connecting fleet signals, data discovery, curation, annotation, model training, evaluation, and performance measurement. Manages a multidisciplinary team of data science, data engineering, and labeling professionals. Drives automated annotation, intelligent mining of rare and safety-critical scenarios, log selection and storage, and rigorous tradeoffs among data quality, cost, speed, and scale. Partners with machine learning, metrics, evaluation, and infrastructure teams to improve autonomous-driving models.
Summary Generated by Built In

Perception data is core to how Zoox’s robotaxis understand the world, and as Senior Manager of Perception Data, you will own the flywheel that turns that data into safer, smarter driving. 

You will lead our perception data organization, spanning data science, data engineering, and data labeling, and own how we mine logs, automate annotation, feed high value data into our models, and close the loop through analysis and measurement. The most valuable examples in our corpus are often the hardest to find: rare behaviors, unusual interactions, safety critical events, and the long tail of real world urban driving. Your role is not only to build the systems that process this data, but to decide what data matters and why, and to build the learning loop that lets Zoox improve model performance faster. 

This is an opportunity for a leader who blends strategic thinking with strong execution, has done it before at scale, and knows how to partner with ML leaders, metrics pipelines, and infrastructure teams.

In this role, you will...

  • Own the perception data flywheel. Run the learning loop from real world fleet signals and model behavior through data discovery, curation, and enrichment into training, evaluation, and measurement.
  • Lead multidisciplinary teams. Manage and develop a 10+ person team of data science, data engineering and data labeling, setting priorities and raising the bar on execution.
  • Automate annotation at scale. Drive auto annotation and auto labeling pipelines, reducing manual cost while improving label quality and throughput.
  • Build advanced data miners. Develop intelligent approaches to surfacing rare, surprising, and safety critical scenarios in very large datasets, using techniques such as embeddings, semantic search, learned representations, and model driven data selection.
  • Own log selection and storage. Define how we select, store, and retrieve fleet logs so the right data reaches our models efficiently and economically.
  • Connect data to model performance. Establish how we measure the value of data and make rigorous trade offs across quality, accuracy, speed, cost, and scale.
  • Close the loop. Feed curated data into model training and evaluation, then analyze outcomes to continuously refine what we collect and label.
  • Partner cross functionally. Work closely with ML, metrics and evaluation, and infrastructure teams to keep the flywheel running reliably at scale.

Qualifications

  • Track record of building and leading high performing technical teams (data science, data engineering, ML, or labeling), including managing managers or senior individual contributors.
  • Deep technical expertise in computer vision, video, multimodal AI, or related perception problems.
  • Experience leading large scale data capabilities that directly influence model training, evaluation, and performance.
  • Strong intuition for what makes data valuable, with experience in data discovery, selection, curation, and enrichment at scale.
  • Proven execution at scale, with strong technical and commercial judgment across quality, speed, cost, and build versus buy trade offs.
  • Ability to move between strategy and technical detail, set direction in ambiguity, and influence senior technical and business stakeholders. 

Bonus Qualifications

  • Autonomous driving, robotics, or embodied AI.
  • Large scale video, multimodal, or foundation model training.
  • Semantic search, embeddings, active learning, auto labeling, or other approaches to intelligent data selection and enrichment.
  • Large scale real world data acquisition across fleets, partners, or multiple geographies.

Skills Required

  • Track record of building and leading high-performing technical teams in data science, data engineering, machine learning, or labeling
  • Experience managing managers or senior individual contributors
  • Deep technical expertise in computer vision, video, multimodal AI, or related perception problems
  • Experience leading large-scale data capabilities that directly influence model training, evaluation, and performance
  • Experience with data discovery, selection, curation, and enrichment at scale
  • Proven execution at scale with technical and commercial judgment across quality, speed, cost, and build-versus-buy tradeoffs
  • Ability to set strategy, navigate ambiguity, move between strategic and technical detail, and influence senior technical and business stakeholders
  • Experience in autonomous driving, robotics, or embodied AI
  • Experience with large-scale video, multimodal, or foundation model training
  • Experience with semantic search, embeddings, active learning, auto-labeling, or intelligent data selection and enrichment
  • Experience with large-scale real-world data acquisition across fleets, partners, or multiple geographies

Zoox Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Zoox and has not been reviewed or approved by Zoox.

  • Healthcare Strength — Healthcare is extensive, with broad medical and vision options, company‑paid disability coverage, and multiple mental‑health resources. Feedback suggests coverage breadth and auxiliary programs support a wide range of needs.
  • Parental & Family Support — Family supports include paid parental leave, additional pregnancy disability time, fertility coverage, and adoption/surrogacy assistance. Backup care and family‑oriented programs further reinforce support across life stages.
  • Wellbeing & Lifestyle Benefits — Day‑to‑day perks are robust, including free daily meals, fitness subsidies, commuter support, and on‑site amenities. Feedback suggests these lifestyle benefits enhance convenience and workplace experience, especially for office‑based roles.

Zoox Insights

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The Company
HQ: Foster City, CA
2,900 Employees
Year Founded: 2014

What We Do

Zoox is an autonomous mobility company that was founded to provide a safer, cleaner, and more enjoyable future on the road. To achieve that goal, the company has spent the past 10 years creating a purpose-built robotaxi that gives the world a better way to ride.

Why Work With Us

At Zoox, we are working to solve one of the greatest technological challenges of our generation. From the beginning, we have been focused on our goal of reimagining transportation from the ground up. We are a mission-driven community of innovators working together to create a safer, cleaner, and more enjoyable future on the road.

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